Back

fsbrain: an R package for the visualization ofstructural neuroimaging data

Schaefer, T.; Ecker, C.

2020-09-20 neuroscience
10.1101/2020.09.18.302935 bioRxiv
Show abstract

SummaryWe introduce fsbrain, an R package for the visualization of neuroimaging data. The package can be used to visualize vertex-wise and region-wise morphometry data, parcellations, labels and statistical results on brain surfaces in three dimensions (3D). Voxel data can be displayed in lightbox mode. The fsbrain package offers various customization options and produces publication quality plots which can be displayed interactively, saved as bitmap images, or integrated into R notebooks. Availability and ImplementationThe software, source code and documentation are available under the MIT license at https://github.com/dfsp-spirit/fsbrain. Releases can be installed directly from the Comprehensive R Archive Network (CRAN). Contacttim.schaefer@kgu.de

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
NeuroImage
○ 903 papers in training set
Top 0.9%
15.3%
Similar papers in this journal
2
Neuroinformatics
○ 46 papers in training set
Top 0.1%
9.8%
Similar papers in this journal
3
Frontiers in Neuroinformatics
○ 41 papers in training set
Top 0.1%
8.9%
Similar papers in this journal
4
Journal of Open Source Software
● 25 papers in training set
Top 0.1%
7.9%
Similar papers in this journal
5
eneuro
● 439 papers in training set
Top 1%
5.5%
Similar papers in this journal
6
Human Brain Mapping
○ 329 papers in training set
Top 1%
4.9%
50% of probability mass above
7
Aperture Neuro
● 20 papers in training set
Top 0.1%
4.9%
8
Cerebral Cortex
◐ 396 papers in training set
Top 2%
3.5%
9
Imaging Neuroscience
● 282 papers in training set
Top 2%
3.1%
10
Journal of Neuroscience Methods
○ 122 papers in training set
Top 0.7%
2.7%
11
eLife
● 5828 papers in training set
Top 40%
2.7%
12
Brain Structure and Function
○ 93 papers in training set
Top 0.4%
2.5%
13
Developmental Cognitive Neuroscience
○ 96 papers in training set
Top 0.5%
1.9%
14
SoftwareX
○ 15 papers in training set
Top 0.1%
1.7%
15
PLOS ONE
● 5266 papers in training set
Top 48%
1.5%
16
PLOS Computational Biology
● 1863 papers in training set
Top 15%
1.5%
17
Nature Protocols
○ 33 papers in training set
Top 0.3%
1.3%
18
Bioinformatics
◐ 1204 papers in training set
Top 7%
1.3%
19
Network Neuroscience
● 126 papers in training set
Top 1%
1.1%
20
Nature Communications
○ 5641 papers in training set
Top 54%
0.9%
21
Frontiers in Psychiatry
○ 87 papers in training set
Top 2%
0.8%
22
BMC Bioinformatics
○ 457 papers in training set
Top 6%
0.8%
23
Frontiers in Neuroimaging
○ 11 papers in training set
Top 0.2%
0.8%
24
PeerJ
◐ 308 papers in training set
Top 11%
0.8%
25
Scientific Data
○ 209 papers in training set
Top 3%
0.8%
26
Communications Biology
○ 993 papers in training set
Top 30%
0.8%
27
Frontiers in Neuroscience
○ 256 papers in training set
Top 7%
0.6%
28
Scientific Reports
○ 3612 papers in training set
Top 76%
0.6%
29
Nature Methods
○ 385 papers in training set
Top 7%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.